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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Defect-mediated diffusion of implanted Mg in GaN: Suppressing dopant redistribution by sequential thermal and microwave annealing

The diffusion behavior of Mg in Mg/N co-implanted GaN is investigated in response to a set of annealing conditions and methodologies, namely, 1000 °C/30 min thermal anneal, by high-temperature pulsed gyrotron microwave annealing at 1420 or 1500 °C, or by thermal and microwave annealing, sequentially. After 1000 °C annealing, the diffusion of Mg in GaN is found to be negligible, as measured by secondary ion mass spectrometry. Annealing by gyrotron microwave annealing alone induces the diffusion of Mg at a rate on the order of 10 −12 cm 2 /s. However, the use of a thermal anneal before microwave gyrotron annealing reduces this rate by an order of magnitude to 10 −13 cm 2 /s. We find that a model that considers Mg diffusion from an inhomogeneous medium that contains a defect-rich implanted region near-surface to a relatively pristine region below the implant range better explains the observed diffusion behavior than a conventional model that assumes a homogeneous medium. By analyzing the diffusion behavior using the Boltzmann–Matano method, we present a discussion of reduction in [V Ga ] by thermal annealing at 1000 °C, leading to a suppressed diffusion coefficient during subsequent high-temperature annealing relative to diffusion after 1420/1500 °C annealing alone. This effect holds potential for improvement in the precision of selectively doped regions for future applications based on the (Al)GaN material system. An improved field profile control in real devices can increase the breakdown and current-handling capabilities in power electronic applications.

Meyers, V.↗

Electric Field Control of Phonon Lifetimes and Thermal Conductivity in Relaxor-Based Ferroelectric

The demand for high energy efficiency drives intense interest in thermal-management technology. Phonons are a major contributor to heat transfer in solids and controlling them through external stimuli is a key challenge for thermal management due to their weak interactions with applied fields. We report significant changes in phonon transport with the application of an electric field over a broad temperature range in a relaxor-based ferroelectric using neutron-scattering and -transport measurements. Phonon lifetimes increase along the applied poling field and this results in a tripling of the thermal conductivity in that direction. We also observe a suppression of nanoscale antiferroelectric fluctuations along the poling direction and argue that this increases the phonon lifetimes. Our results highlight a promising yet underexplored route to realistic solid-state heat switching from electric-field-modified nanostructures altering the phonon lifetimes in disordered functional materials.

Phonons↗

Fabrication of single color centers in sub-50 nm nanodiamonds using ion implantation

Diamond color centers have been widely studied in the field of quantum optics. The negatively charged silicon vacancy (SiV – ) center exhibits a narrow emission linewidth at the wavelength of 738 nm, a high Debye–Waller factor, and unique spin properties, making it a promising emitter for quantum information technologies, biological imaging, and sensing. In particular, nanodiamond (ND)-based SiV – centers can be heterogeneously integrated with plasmonic and photonic nanostructures and serve as in vivo biomarkers and intracellular thermometers. Out of all methods to produce NDs with SiV – centers, ion implantation offers the unique potential to create controllable numbers of color centers in preselected individual NDs. However, the formation of single color centers in NDs with this technique has not been realized. We report the creation of single SiV– centers featuring stable high-purity single-photon emission through Si implantation into NDs with an average size of ~20 nm. We observe room temperature emission, with zero-phonon line wavelengths in the range of 730–800 nm and linewidths below 10 nm. Our results offer new opportunities for the controlled production of group-IV diamond color centers with applications in quantum photonics, sensing, and biomedicine.

36 MATERIALS SCIENCE↗

Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Water Freezes at Near-Zero Temperatures Using Carbon Nanotube-Based Electrodes under Static Electric Fields

Although static electric fields have been effective in controlling ice nucleation, the highest freezing temperature ( T f ) of water that can be achieved in an electric field ( E ) is still uncertain. In this study, we performed a systematic study of the effect of an electric field on water freezing by varying the thickness of a dielectric layer and the voltage across it in an electrowetting system. Results show that T f first increases sharply with E and then reaches saturation at –3.5 °C after a critical value E of 6 × 10 6 V/m. Using classical heterogeneous nucleation theory, it is revealed that this behavior is due to saturation in the contact angle of the ice embryo with the underlying substrate. Finally, we show that it is possible to overcome this freezing saturation by controlling the uniformity of the electric field using carbon nanotubes. We achieve a T f of –0.6 °C using carbon nanotube-based electrodes with an E of 3 × 10 7 V/m. This work sheds new light on the control of ice nucleation and has the potential to impact many applications ranging from food freezing to ice production.

25 ENERGY STORAGE↗

Unveiling mechanism of surface-guided platinum nanowire growth

We report surface-guided growth of non-planar nanowires on functional substrates offers the new opportunity to precisely control their diameter, length, density and alignment, which will greatly benefit their direct integration into practical devices for large-scale applications. However, control of noble metal nanowires growth and arrangement remains a great challenge, and the mechanistic understanding is still limited. Herein, we choose Pt as a model material system to study the synthesis conditions required to control the in situ growth of aligned Pt nanowires on flat titanium substrate via a one-step and room-temperature green chemical synthesis process in aqueous solution. Most importantly, it is for the first time discovered that ordered nanoarrays and self-assembled nanoflowers can be directly grown on flat Ti substrate by merely adjusting the reaction times, without use of any soft/hard templates, surfactants and organic solvents. The proposed surface-guided growth mechanisms for nanoarray and nanoflower formation in this study may shed light on understanding of oriented arrangement/assembly of one-dimensional Pt nanowires into desirable morphologies for a variety of practical device applications.

Pt nanoflower↗

Generative Physics-Informed Neural Network Solving Multi-Scale and Multi-Phase Plasma Chemical Flow Field

Low-temperature plasmas (LTPs) are non-equilibrium systems with near-room-temperature gas and highly energetic electrons. This makes them ideal for delicate applications in biomedicine and semiconductor manufacturing, enabling processes like wound healing, sterilization, etching, and plasma-enhanced chemical vapor deposition without thermal damage. However, LTPs involve complex chemistries, with hundreds of species and thousands of reactions, complicating their diagnosis, prediction, and control. Conventional diagnostics, such as Fourier-transform infrared spectroscopy (FTIR), laser-induced fluorescence (LIF), and optical emission spectroscopy (OES), offer limited species detection, while mass spectrometry (MS) struggles with low-sensitivity species. Additionally, LTP simulations face multi-scale challenges, as macroscopic fluid dynamics and microscopic particle collisions operate on vastly different timescales. To address these issues, we developed an artificial intelligence (AI) based diagnostic system: a generative physics-informed neural network (PINN-Gen) that can predict spatially resolved species concentrations and temperatures in LTPs by integrating experimental data from planar LIF with microscopic plasma chemical kinetics and macroscopic fluid mechanics, including plasma-liquid interactions at the interface between two phases. PINN-Gen solves no equations but checks the errors of physical laws by substituting the output from neural network, and the comparison with the experimental results. Thus, it naturally avoids the multi-scale difficulty of numerical simulations and predicts the results of conventionally unsolvable multi-scale and multi-phase problems. The real-time prediction will be robust due to the physical information used in the training of such a neural network, and only very limited input of condition required due to its generative feature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Micro-mechanical investigation of the thermo-mechanical properties of micro-architectured tungsten coatings

The thermo-mechanical response of micro-architectured tungsten coatings is characterized in the temperature range of 293 to 673 K using both in situ micro-compression experiments inside a scanning electron microscope (SEM) as well as image-based crystal plasticity finite element method (CPFEM) simulations. The experiments were conducted on micropillar-like specimens that were focus ion beam milled into the coatings, while the simulations were conducted on columnar-grained micropillar simulation cells constructed based on the statistics of the coating’s microstructure. The experimental results show that the stress–strain response and deformation mode exhibit a strong temperature-dependence. At room temperature, catastrophic failure is observed shortly after yield and is manifested in the form of intergranular fracture and buckling of individual columnar grains. With increasing temperature, this catastrophic failure is gradually suppressed and the material exhibits a steadier strain hardening response at 693 K. The CPFEM simulations are also shown to be in good agreement with the experimental results, and these simulations indicate that the material response is strongly influenced by the local crystallographic anisotropy and microstructure inhomogeneity. Furthermore, the simulations capture the underlying mechanisms that control the temperature-dependent transition in deformation mode. The current results highlight that the micro-architectured microstructure offers a great combination of excellent mechanical strength and structural integrity at elevated temperatures, which is of importance for high temperature applications.

36 MATERIALS SCIENCE↗

Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods

Simulation of reservoir releases plays a critical role in social-economic functioning and our nation's security. How-ever, it is challenging to predict the reservoir release accurately because of many influential factors from natural environments and engineering controls such as the reservoir inflow and storage. Moreover, climate change and hydrological intensification causing the extreme precipitation and temperature make the accurate prediction of reservoir releases even more challenging. Machine learning (ML) methods have shown some successful applications in simulating reservoir releases. However, previous studies mainly used inflow and storage data as inputs and only considered their short-term influences (e.g, previous one or two days). In this work, we use long short-term memory (LSTM) networks for reservoir release prediction based on four input variables including inflow, storage, precipitation, and temperature and consider their long-term influences. We apply the LSTM model to 30 reservoirs in Upper Colorado River Basin, United States. We analyze the prediction performance using six statistical metrics. More importantly, we investigate the influence of the input hydrometeorological factors, as well as their temporal effects on reservoir release decisions. Results indicate that inflow and storage are the most influential factors but the inclusion of precipitation and temperature can further improve the prediction of release especially in low flows. Additionally, the inflow and storage have a relatively long-term effect on the release. These findings can help optimize the water resources management in the reservoirs.

Fan, Ming↗

Scaling, rotation, and channeling behavior of helical and skyrmion spin textures in thin films of Te-doped Cu 2 OSeO 3

Topologically nontrivial spin textures such as vortices, skyrmions, and monopoles are promising candidates as information carriers for future quantum information science. Their controlled manipulation including creation and annihilation remains an important challenge toward practical applications and further exploration of their emergent phenomena. Here, we report controlled evolution of the helical and skyrmion phases in thin films of multiferroic Te-doped Cu 2 OSeO 3 as a function of material thickness, dopant, temperature, and magnetic field using in situ Lorentz phase microscopy. We report two previously unknown phenomena in chiral spin textures in multiferroic Cu 2 OSeO 3 : anisotropic scaling and channeling with a fixed-Q state. The skyrmion channeling effectively suppresses the recently reported second skyrmion phase formation at low temperature. Our study provides a viable way toward controlled manipulation of skyrmion lattices, envisaging chirality-controlled skyrmion flow circuits and enabling precise measurement of emergent electromagnetic induction and topological Hall effects in skyrmion lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Wavelength-tunable infrared chiral metasurfaces with phase-change materials

Optical phase-change materials exhibit tunable permittivity and switching properties during phase transition, which offers the possibility of dynamic control of optical devices. Here, a wavelength-tunable infrared chiral metasurface integrated with phase-change material GST-225 is demonstrated with the designed unit cell of parallelogram-shaped resonator. By varying the baking time at a temperature above the phase transition temperature of GST-225, the resonance wavelength of the chiral metasurface is tuned in the wavelength range of 2.33 µm to 2.58 µm, while the circular dichroism in absorption is maintained around 0.44. The chiroptical response of the designed metasurface is revealed by analyzing the electromagnetic field and displacement current distributions under left- and right-handed circularly polarized (LCP and RCP) light illumination. Moreover, the photothermal effect is simulated to investigate the large temperature difference in the chiral metasurface under LCP and RCP illumination, which allows for the possibility of circular polarization-controlled phase transition. The presented chiral metasurfaces with phase-change materials offer the potential to facilitate promising applications in the infrared regime, such as chiral thermal switching, infrared imaging, and tunable chiral photonics.

36 MATERIALS SCIENCE↗

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries

Due to the growth of electric vehicle and stationary energy storage markets, the production and use of lithium-ion batteries has grown exponentially in recent years. For many of these applications, large-format lithium-ion batteries are being utilized, as large cells have less inactive material relative to their energy capacity and require fewer electrical connections to assemble into packs. And especially for stationary energy storage systems, where energy delivered is the only revenue source, the economics of these battery systems is highly dependent on cell lifetime. However, testing of large-format lithium-ion batteries is time consuming and requires high current channels and large testing chambers, making information on the performance of commercial, large-format lithium-ion batteries hard to come by. Here, accelerated aging test data from four commercial large-format lithium-ion batteries is reported. These batteries span both NMC-Gr and LFP-Gr cell chemistries, pouch and prismatic formats, and a range of cell designs with varying power capabilities. Accelerated aging test results are analyzed to examine both cell performance, in terms of efficiency and thermal response under load, as well as cell lifetime. Cell thermal response is characterized by measuring temperature during cycle aging, which is used to calculated a normalized thermal resistance value that may help estimate both cell cooling needs or to help extrapolate aging test results to different thermal environments. Cell lifetime is evaluated qualitatively, considering simply the average calendar and cycle life across a range of conditions, as well as quantitatively, using statistical modeling and machine-learning methods to identify predictive aging models from the accelerated aging data. These predictive aging models are then used to investigate cell sensitivities to stressors, such as cycling temperature, voltage window, and C-rate, as well as to predict cell lifetime in various stationary storage applications. Results from this work show that cell lifetime and sensitivity to aging conditions varies substantially across commercial cells, necessitating testing for specific cell formats to make quantitative lifetime predictions. That being said, all commercial cells tested here are predicted to reach at least 10-year lifetimes for stationary storage applications. Based on the aging test results and modeling, some cells are expected to be relatively insensitive to temperature and use-case, making them suited for simple use cases with little or no thermal management and simple controls, while the lifetime of other cells could be extended to 20+ years if operated with thermal management and degradation-aware controls.

battery↗

Additive-Mixing Fuel Injection (AMFI): A device for robust control and improved performance of high-efficiency LTGC engines

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies with very low NOx and particulate emissions. Despite these major advantages, methods for controlling LTGC combustion timing, achieving robust autoignition, and good low-load performance have challenged the development of practical LTGC engines. A key reason is that the ideal reactivity of the fuel varies with operating conditions, with low-reactivity fuels working well at high loads and higher-reactivity fuels working better at low loads. This article introduces a new technique called Additive Mixing Fuel Injection (AMFI) that adjusts the reactivity of the gasoline to obtain good performance over the operating map. Moreover, AMFI can provide robust combustion-timing control because it precisely meters very small amounts (0.01–0.6 mm 3 ) of an ignition-enhancing additive into the fuel each engine cycle. The additive used was 2-ethylhexyl nitrate (EHN), a common, inexpensive diesel-fuel ignition improver, but other additives could be used. Because additive amounts are so small, a 2-gal reservoir would be sufficient for medium-duty applications with refilling only at service intervals of about 8000 mi. The AMFI system has been installed on a single-cylinder LTGC research engine and demonstrated to provide robust combustion-timing control over wide ranges of combustion phasing, fueling rate, intake boost, engine speed, and intake temperature. AMFI also increases the fuel’s reactivity sufficiently to greatly reduce or eliminate the need for charge heating, simplifying engine design and significantly increasing thermal efficiency and the maximum load at low-boost conditions. The nitrogen in the EHN produced a modest increase in NOx, but it was mitigated by lower intake temperatures, and NOx emissions remained very low. Finally, the additive increases the sensitivity of autoignition reactions to variations in the local fuel/air mixture within the charge. This allows the use of controlled fuel stratification for improved LTGC-engine performance, and its potential to improve low-load operation was demonstrated.

Dec, John E.↗

Wind Energy Forecasting with the Weather Research and Forecasting Model

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Siemens Energy, Inc. (Siemens) to develop a wind resource forecasting tool. LLNL was to develop an independent high-resolution mesoscale modeling capability forecasting tool that could be implemented in conjunction with existing wind farm control and monitoring software to provide forecasting of wind resources using local observations of winds and temperature. Research with LLNL’s state-of-the-art large-eddy simulation meteorological prediction model, based on the community WRF model and innovative turbulence parameterizations, would improve that model’s applicability to large wind farms offshore and in complex terrain. The modeling capability would include uncertainty quantification. Finally, the application of the modeling tool and existing global climate change predictions would enable the delineation of the likely effects of climate change on wind resources. Siemens was to provide high time resolution hub-height wind speed and other meteorological data streams, including temperature profiles from wind farms, for LLNL to incorporate into the modeling system, to validate and tune this forecasting model for their locations of interest. These data streams would also be used for longer-term studies of correlations of wind resources to climate oscillations to indicate how long-term climate change trends may affect the available wind resource. Siemens would also provide information and observations of turbine wakes for incorporation into the modeling tool. By implementing state-of-the-art turbulence parameterizations into a simulation model and/or ensembles of simulation models, and by integrating real-time hub height wind speed and other meteorological datastreams from wind farms into that model or ensemble of models, LLNL would develop a forecasting tool that could be implemented by Siemens as an add-on to existing wind farm control and monitoring software to provide owners with useful resource forecasting. The desired outcome was that the accuracy level of the output would be sufficient to substantiate power output commitments. The final deliverable for this work would consist of a document outlining the algorithms and software tools that could be integrated into Siemens Wind Park Supervisor.

17 WIND ENERGY↗

One-Pot Synthesis of Melamine Formaldehyde Resin-Derived N-Doped Porous Carbon for CO 2 Capture Application

The design and synthesis of porous carbons for CO 2 adsorption have attracted tremendous interest owing to the ever-soaring concerns regarding climate change and global warming. Herein, for the first time, nitrogen-rich porous carbon was prepared with chemical activation (KOH) of commercial melamine formaldehyde resin (MF) in a single step. It has been shown that the porosity parameters of the as-prepared carbons were successfully tuned by controlling the activating temperature and adjusting the amount of KOH. Thus, as-prepared N-rich porous carbon shows a large surface area of 1658 m 2 /g and a high N content of 16.07 wt%. Benefiting from the unique physical and textural features, the optimal sample depicted a CO 2 uptake of up to 4.95 and 3.30 mmol/g at 0 and 25 °C under 1 bar of pressure. More importantly, as-prepared adsorbents show great CO 2 selectivity over N 2 and outstanding recyclability, which was prominently important for CO 2 capture from the flue gases in practical application. An in-depth analysis illustrated that the synergetic effect of textural properties and surface nitrogen decoration mainly determined the CO 2 capture performance. However, the textural properties of carbons play a more important role than surface functionalities in deciding CO 2 uptake. In view of cost-effective synthesis, outstanding textural activity, and the high adsorption capacity together with good selectivity, this advanced approach becomes valid and convenient in fabricating a unique highly efficient N-rich carbon adsorbent for CO 2 uptake and separation from flue gases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Methods of controllable interstitial oxygen doping in niobium

A method for vacuum heat treating Nb, such as is used in superconducting radio frequency cavities, to engineer the interstitial oxygen profile with depth into the surface to conveniently optimize the low-temperature rf surface resistance of the material. An example application is heating of 1.3 GHz accelerating structures between 250-400° C. to achieve a very high quality factor of 5×1010 at 2.0 K. With data supplied by secondary ion mass spectrometry measurements, application of oxide decomposition and oxygen diffusion theory was applied to quantify previously unknown parameters crucial in achieving the oxygen alloy concentration profiles required to optimize the rf surface resistance. RF measurements of vacuum heat treated Nb superconducting radio frequency cavities confirmed the minimized surface resistance (higher Q0) previously expected only from 800° C. diffusive alloying with nitrogen.

Palczewski, Ari D.↗

Nucleation and Antiphase Twin Control in Bi 2 Se 3 via Step‐Terminated Al 2 O 3 Substrates

The epitaxial synthesis of high-quality 2D layered materials is an essential driver of both fundamental physics studies and technological applications. Bi 2 Se 3 , a prototypical 2D layered topological insulator, is sensitive to defects imparted during the growth, either thermodynamically or due to the film-substrate interaction. Here, in this study, it is shown that step-terminated Al 2 O 3 substrates with a high miscut angle (3°) can effectively suppress a particular hard-to-mitigate defect, the antiphase twin. Systematic investigations across a range of growth temperatures and substrate miscut angles confirm that atomic step edges act as preferential nucleation sites, stabilizing a single twin domain. First-principles calculations suggest that there is a significant energy barrier for twin boundary formation at step edges, supporting the experimental observations. Detailed structural characterization indicates that this twin-selectivity is lost through the mechanism of the 2D layers overgrowing the step edges, leading to higher twin density as the thickness increases. These findings highlight the complex energy landscape unique to 2D materials that is driven by the interplay between substrate properties, nucleation dynamics, and defect formation, and overcoming and controlling these are critical to improve material quality for quantum and electronic applications.

36 MATERIALS SCIENCE↗

Thermal hydraulic characteristics of liquid sodium and supercritical CO 2 in a diffusion bonded heat exchanger

Compact heat exchangers are being examined for use in advanced, high-temperature nuclear or concentrated solar power plants to improve thermal efficiencies and reduce capital costs. At the time of this work, no experimental investigation of liquid sodium in the popular diffusion-bonded heat exchanger design had been performed. Herein this paper describes the thermal-hydraulic and overall operations performance observed during testing of a 316/L stainless steel “zig-zag” microchannel heat exchanger operating between a (0.5 kg/s) sodium loop and a (0.3 kg/s) recuperated supercritical CO 2 system with outlet conditions up to 550 °C at 16 MPa. Observed pressure drop is presented in the form of an effective friction factor correlation which aligns closely with recent experimental data. The thermal performance of this heat exchanger, measured by its overall conductance under various flow conditions, was decomposed to examine the independent convection behaviors of both the CO 2 and sodium streams. These results are presented in the form of Nusselt correlations fitted to the experimental data. The sodium heat transfer correlation aligns closely with the widely accepted Lubarsky-Kaufman correlation, while the CO 2 heat transfer correlation lies between previous correlations developed by computational and experimental methods. This was the first long-duration use of sodium in a microchannels (~1.8 mm hydraulic diameter) heat exchanger. The use of an oxide control system enabled trouble-free operation of the heat exchanger for over 150 h of high-temperature operation. This first-of-a-kind demonstration using liquid sodium and supercritical carbon dioxide shows great promise for further application of this technology in advanced nuclear or solar power plants.

42 ENGINEERING↗